我读到我可以从 lucene 索引创建 mahout 向量,该向量可用于应用 mahout 聚类算法。http://cwiki.apache.org/confluence/display/MAHOUT/Creating+Vectors+from+Text

我想在 Lucene 索引中的文档中应用 K 均值聚类算法,但不清楚如何应用此算法(或层次聚类)来提取这些文档中有意义的聚类。

在此页面中 http://cwiki.apache.org/confluence/display/MAHOUT/k-Means表示该算法接受两个输入目录:一个用于数据点,一个用于初始聚类。我的数据点是文件吗?我如何“声明”这些是我的文档(或其向量),只需将它们进行聚类?

提前为我糟糕的语法感到抱歉

谢谢

有帮助吗?

解决方案

如果你有载体,可以运行KMeansDriver。以下是相同的帮助。

Usage:
 [--input <input> --clusters <clusters> --output <output> --distance <distance>
--convergence <convergence> --max <max> --numReduce <numReduce> --k <k>
--vectorClass <vectorClass> --overwrite --help]
Options
  --input (-i) input                The Path for input Vectors. Must be a
                                    SequenceFile of Writable, Vector
  --clusters (-c) clusters          The input centroids, as Vectors.  Must be a
                                    SequenceFile of Writable, Cluster/Canopy.
                                    If k is also specified, then a random set
                                    of vectors will be selected and written out
                                    to this path first
  --output (-o) output              The Path to put the output in
  --distance (-m) distance          The Distance Measure to use.  Default is
                                    SquaredEuclidean
  --convergence (-d) convergence    The threshold below which the clusters are
                                    considered to be converged.  Default is 0.5
  --max (-x) max                    The maximum number of iterations to
                                    perform.  Default is 20
  --numReduce (-r) numReduce        The number of reduce tasks
  --k (-k) k                        The k in k-Means.  If specified, then a
                                    random selection of k Vectors will be
                                    chosen as the Centroid and written to the
                                    clusters output path.
  --vectorClass (-v) vectorClass    The Vector implementation class name.
                                    Default is SparseVector.class
  --overwrite (-w)                  If set, overwrite the output directory
  --help (-h)                       Print out help

更新:从HDFS结果目录到本地FS。然后使用ClusterDumper实用程序获取的文件集群,并列出该集群。

其他提示

一个非常好的方法在这里:将 apache mahout 与 apache lucene 集成

@ maiky 你可以阅读更多关于阅读的输出,该页面使用clusterdump工具 - > HTTPS ://cwiki.apache.org/confluence/display/MAHOUT/Cluster+Dumper

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